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 DeepSeek-V2-MoE架构和计算流程.pdf 10,032.5 kB 1 14-May-2025 09:51 103.243.180.9
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 MoR.pptx 458.5 kB 1 19-Sep-2025 16:58 14.155.114.124
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 Neural Logic Machines (NLM) 论文... 239.9 kB 1 02-Mar-2026 09:52 14.153.56.177
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 OneFlow技术年货（2023）公众号 .pdf 92,656.5 kB 1 15-Oct-2024 09:42 14.153.207.59
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 OpenAI 机械可解释性新范式解析(1).pptx 1,406.6 kB 1 25-Dec-2025 10:54 14.155.111.65
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 RAG分享.pptx 45,303.6 kB 1 24-Oct-2024 09:26 14.153.207.13
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 Tranfromer解码器分享.pdf 40,589.8 kB 1 24-Oct-2024 09:34 14.153.207.13
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 Vision Transformer.pptx 1,720.8 kB 2 19-Sep-2025 16:59 14.155.114.124
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 关于训练.jpg 7,252.1 kB 1 14-Feb-2025 17:07 14.153.82.186
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 基于超尺度全域观察者的物理统一理论.pdf 433.9 kB 1 06-May-2026 18:17 14.155.118.116
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 基于超尺度全局观察者的物理统一理论.pdf 679.6 kB 4 07-May-2026 09:29 14.155.118.116
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 扩散模型.pptx 1,176.6 kB 1 19-Sep-2025 17:08 14.155.114.124
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 数据传递---以纯文本Q&A问答对格式.pptx 36,019.1 kB 1 07-Nov-2024 14:37 14.155.107.185
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 旋转位置编码.pptx 470.5 kB 1 19-Sep-2025 16:58 14.155.114.124
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At line 5 changed one line
!!维特根斯坦说：语言的边界就是思想的边界
!!维特根斯坦说：语言的边界就是世界的边界
At line 18 changed one line
涌现本质是大模型通过大量数据训练，构建的概念世界结构，已经理解到了世界本质。学习到了高维空间的规律
涌现本质是大模型通过大量数据训练，构建的概念世界结构，已经理解到了世界本质。学习到了高层次的规律
At line 26 changed 4 lines
!!反向传播改造分两部分：
全量反向传播和增量反向传播\\
全量反向传播通过损失设计引导参数形成有序的熵最小的结构\\
增量反向传播通过有序的结构快速定位反向传播
!!写作之难，在于把网状的思考，用树状结构，体现在线性展开的语句里。
生成内容之难，正如[斯蒂芬·平克|https://sspai.com/post/66959]如是说，而把线性空间里的语句，梳理成树状结构，然后嵌入网状的理解结构里，就是阅读之难，也是模型训练之难
At line 29 added 6 lines
!![大模型本质是用有限参数（符号）表达无限的宇宙|nature]
!![基于超尺度全域观察者的物理统一理论——量子力学与经典力学、随机性与确定性的融合的哲学思考|http://www.mandelbrot.cn:8080/JSPWiki/attach/Share/%E5%9F%BA%E4%BA%8E%E8%B6%85%E5%B0%BA%E5%BA%A6%E5%85%A8%E5%B1%80%E8%A7%82%E5%AF%9F%E8%80%85%E7%9A%84%E7%89%A9%E7%90%86%E7%BB%9F%E4%B8%80%E7%90%86%E8%AE%BA.pdf]
!![观察是意识的开始，是智能的自相似递归，能量完成自观察的结果|self-consciousness]
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[生物神经网络精细仿真算法|https://idm.pku.edu.cn/info/1012/1758.htm]
[生物神经网络精细仿真算法|https://idm.pku.edu.cn/info/1012/1758.htm]\\
[精细神经元|https://blog.csdn.net/Fellyhosn/article/details/130048518]\\
[大脑看世界的方式，竟与语言模型惊人一致|https://doi.org/10.1038/s42256-025-01072-0]\\
[知识蒸馏|https://zhuanlan.zhihu.com/p/637108617]\\
[控制论与科学方法论|https://zhuanlan.zhihu.com/p/399765962]\\
[系统论|https://www.cnblogs.com/haohai9309/p/18921515]\\
[非解释性小模型也可以有大模型的能力|https://cloud.tencent.com/developer/article/2335354]\\
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[MiniMax（Google 最新模型）|https://arxiv.org/abs/2501.08313]
[MiniMax（Google 最新模型）|https://arxiv.org/abs/2501.08313]\\
[MOR|https://arxiv.org/pdf/2507.10524v1]\\
[基于MOE的黑箱分时分块训练（非最优解）|https://arxiv.org/abs/2602.11543]\\
[弹性 AI 预训练来自google|https://arxiv.org/pdf/2604.21428v1]\\
At line 75 added 12 lines
!扩散模型
[龙君言|http://www.mandelbrot.cn:8080/JSPWiki/attach/Share/%E6%89%A9%E6%95%A3%E6%A8%A1%E5%9E%8B.pptx]
!VIT分享
[龙君言|http://www.mandelbrot.cn:8080/JSPWiki/attach/Share/Vision%20Transformer.pptx]
!MOR分享
[龙君言|http://www.mandelbrot.cn:8080/JSPWiki/attach/Share/MoR.pptx]
!旋转位置编码分享
[龙君言|http://www.mandelbrot.cn:8080/JSPWiki/attach/Share/%E6%97%8B%E8%BD%AC%E4%BD%8D%E7%BD%AE%E7%BC%96%E7%A0%81.pptx]
At line 69 changed one line
[余烨|https://icnwnitmcdqj.feishu.cn/wiki/EmlBwvMwGiqGHZkySvSckLENnMd?from=from_copylink]
[余烨的分享|https://icnwnitmcdqj.feishu.cn/wiki/EmlBwvMwGiqGHZkySvSckLENnMd?from=from_copylink]
At line 71 changed one line
!![自成长模型|selfGrowModel]
!!知识蒸馏
[敖博士的分享|https://icnwnitmcdqj.feishu.cn/wiki/P5NkwsGYdiD3QLkuVCecejJ1n6e?from=from_copylink]
At line 102 added 9 lines
!!OpenAI的机械可解释分享
[余烨的分享|http://www.mandelbrot.cn:8080/JSPWiki/attach/Share/OpenAI%20%E6%9C%BA%E6%A2%B0%E5%8F%AF%E8%A7%A3%E9%87%8A%E6%80%A7%E6%96%B0%E8%8C%83%E5%BC%8F%E8%A7%A3%E6%9E%90%281%29.pptx]
!!基于MLP神经网络的规则模型实现
[余烨的分享|http://www.mandelbrot.cn:8080/JSPWiki/attach/Share/Neural%20Logic%20Machines%20%28NLM%29%20%E8%AE%BA%E6%96%87%E8%AE%B2%E8%A7%A3.pptx]
!![可解释的自成长模型是通向AGI的唯一路径|selfGrowModel]
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180 25-May-2026 14:56 5.311 kB 88.210.36.107 to previous
179 25-May-2026 09:30 5.29 kB 14.155.109.39 to previous | to last
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177 06-May-2026 19:27 5.255 kB 88.210.36.109 to previous | to last
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